Carbohydrate and insulin response -
Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Mirrahimi A, de Souza RJ, Chiavaroli L, et al. Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts.
J Am Heart Assoc. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic index and glycemic load values: Buyken, AE, Goletzke, J, Joslowski, G, Felbick, A, Cheng, G, Herder, C, Brand-Miller, JC.
Association between carbohydrate quality and inflammatory markers: systematic review of observational and interventional studies. The American Journal of Clinical Nutrition Am J Clin Nutr. AlEssa H, Bupathiraju S, Malik V, Wedick N, Campos H, Rosner B, Willett W, Hu FB.
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As blood sugar levels rise, the pancreas produces insulin, a hormone that prompts cells to absorb blood sugar for energy or storage. As cells absorb blood sugar, levels in the bloodstream begin to fall. When this happens, the pancreas start making glucagon, a hormone that signals the liver to start releasing stored sugar.
This interplay of insulin and glucagon ensure that cells throughout the body, and especially in the brain, have a steady supply of blood sugar. Type 2 diabetes usually develops gradually over a number of years, beginning when muscle and other cells stop responding to insulin.
This condition, known as insulin resistance, causes blood sugar and insulin levels to stay high long after eating.
Over time, the heavy demands made on the insulin-making cells wears them out, and insulin production eventually stops. Complex carbohydrates: These carbohydrates have more complex chemical structures, with three or more sugars linked together known as oligosaccharides and polysaccharides.
A washout period of 2—4 weeks separated the feeding periods. During the washout, participants ate their own foods. The macronutrient composition for study diets is presented in Table 1. The increase in fat in the UNSAT diet primarily resulted from an increase in monounsaturated fat from olive, canola, and safflower oils and nuts and seeds.
Protein sources included meat, poultry, egg product substitutes, and dairy; however, most of the increase in the PROT diet came from plant-based sources. The type of carbohydrate in each diet was similar, as indicated by the total dietary glycemic index 68 in CARB diet, 71 in the PROT diet, and 75 in UNSAT diet, relative to the white bread index.
For each diet, there was a 7-day menu cycle. Participants were weighed daily. All meals and snacks were prepared in research kitchens and provided to the participants. Participants were asked to maintain exercise frequency and intensity and to limit alcohol consumption to usual patterns.
Fasting blood samples were collected after an 8—h fast at baseline and at 4 and 6 weeks of each feeding period, for assessment of insulin and glucose levels. Glucose was measured using the enzymatic hexokinase kit from Roche on the Hitachi Insulin was measured using microparticle enzyme immunoassay technology on the Abbott IMx analyzer.
To enhance precision, we averaged the values taken at 4 and 6 weeks to produce one intervention value for each diet in each participant. We assessed insulin sensitivity by calculating the QUICKI quantitative insulin check index measure of insulin sensitivity 8.
As the linear slopes of HOMA change in relation to varying insulin sensitivities, the reciprocal and log transformation of HOMA inherent in QUICKI make it a more flexible measure, usable in normal weight, overweight, and the insulin-resistant state of obese individuals, and more appropriate for the range of BMI in our population 8 , 12 — Statistical analysis was performed using linear regression analysis with generalized estimating equations with exchangeable correlations to account for repeated measures with robust estimation of the variance.
The primary outcome measure is the change in QUICKI index, representing the difference between the index calculated at baseline and after each diet, respectively. The continuous variables for change in QUICKI were approximately normally distributed.
At baseline, we assessed correlations between QUICKI and traditional cardiovascular disease risk factors using Pearson correlation coefficients. There were few data missing; only 4 out of participants did not complete all three intervention diets.
Only participants with complete data were included in the regression analysis. In the initial OmniHeart Trial analysis, there was a change in weight of 1 kg across the first period, although mean end-of-period weights were similar regardless of diet intervention.
To account for any impact on insulin sensitivity from this change in weight and by period, we adjusted for feeding period. To assess for carryover, we lagged exposure by one feeding period and found no evidence of a statistically significant carryover effect.
We tested for interaction between diet and BMI, sex, race, age, and prediabetes status through interaction terms, which were insignificant for all stated variables. We then performed stratified analyses based on BMI category normal, overweight, or obese and clinical status of prediabetes or normoglycemia.
As a sensitivity analysis, we modeled the first period in isolation to examine the effects without preceding intervention. Further sensitivity analyses demonstrated that outliers did not have a marked effect on our regression model. No adjustments were made for multiple testing.
Primary analyses were performed using STATA version Mean BMI was Other baseline characteristics are reported in Table 2. In between-diet comparisons, adjusted for period effects, the QUICKI index increased by a mean of 0.
There were no between-diet differences for glucose or insulin Table 3. Between-diet comparisons of change in QUICKI measure.
Change in QUICKI determined by generalized estimating equations. In models adjusting for feeding period Table 3 , the UNSAT diet increased QUICKI by 0. Similar findings were seen in analyses not adjusted for feeding period.
We found no significant correlation between change in QUICKI and change in weight, change in systolic or diastolic blood pressure, total, HDL, or LDL cholesterol, or triglycerides not presented. The average weight decrease from baseline was similar across all three diets: mean SD 0.
We adhered to conservative guidelines for analysis of subgroups 15 , and as our interaction terms between diet and BMI, diabetes status, age, race, or sex were not significant, we did not highlight subgroup results in Table 3. When stratified by BMI, normal-weight participants experienced an increase in QUICKI with the UNSAT as compared with the CARB diet that trended toward significance 0.
There was no change in those who were overweight 0. There were no differences in the PROT versus CARB or UNSAT versus PROT comparisons. The UNSAT diet increased the QUICKI index from baseline, whereas the CARB and PROT diets did not.
The improvements in insulin sensitivity were both statistically significant and clinically relevant, and this comparative difference between three healthy diets has not previously been demonstrated. These data suggest that an isocaloric diet similar in macronutrient proportions to Mediterranean-style diets may improve insulin sensitivity in patients without type 2 diabetes.
A key feature of this study is the examination of changes in insulin sensitivity by differing macronutrient intake while weight was held constant. The association of weight loss among overweight or obese individuals with increases in insulin sensitivity has been extensively studied 18 — In the OmniHeart Trial, weight change during the three feeding periods was small and not significantly different between intervention diets.
Thus, the results suggest that reducing carbohydrate while increasing unsaturated fat in a healthy diet improves insulin sensitivity in the setting of stable weight.
Interestingly, there was no corresponding improvement when participants consumed the reduced-carbohydrate, increased-protein diet. Hence, the improvement in insulin sensitivity on UNSAT appears to result from an increase in unsaturated fat rather than a decrease in carbohydrate.
We chose QUICKI as our primary measure of insulin sensitivity. Both HOMA and QUICKI indices have been validated as methods to assess insulin sensitivity in comparison with the gold standard hyperinsulinemic-euglycemic glucose clamp 8 , Although both are widely used, the log transformations of fasting insulin and glucose inherent in the construction of QUICKI allow for a better correlation with the gold standard over a wider distribution of fasting insulin values, in both obese and hypertensive patients 8 , 12 , There is evidence to suggest that β-cell dysfunction may occur prior to changes in fasting insulin or glucose levels Investigations into the effects of unsaturated fat— or carbohydrate-rich diets on glycemic control have yielded conflicting results.
An isocaloric feeding trial of participants demonstrated no differences in insulin sensitivity after replacing saturated fatty acids with monounsaturated fats or carbohydrates, regardless of the glycemic index of the diet In this trial, weight was not held constant throughout the feeding periods.
A second randomized trial, comparing a standard carbohydrate-rich diet with one high in fat and reduced carbohydrates, measured both insulin sensitivity and β-cell function. It suggested that a higher-fat, lower-carbohydrate diet may actually lower β-cell responsiveness, whereas dynamic insulin sensitivity measurements remained unaffected Possible reasons for the difference in results are fewer total participants who had a higher average BMI than in our analysis and who had a significant increase in their fasting glucose measurements.
Our trial tested moderate, achievable differences in macronutrients, rather than more extreme changes, such as carbohydrate elimination or ketogenic diets. A high-fat, low-protein, very-low-carbohydrate diet has attracted considerable attention, particularly in the lay press. Although often leading to substantial weight loss, the ketogenic diet, as an extreme of fat-predominant macronutrient composition, may actually be detrimental to overall insulin sensitivity.
In animal studies, dynamic measures of insulin sensitivity have shown an increase in hepatic insulin resistance after consumption of ketogenic diets 26 , Nutrients, other than carbohydrates and unsaturated fat, and behavioral factors might influence insulin sensitivity.
Saturated fatty acids decrease responsiveness of the cell membrane to insulin-mediated actions through a decrease in binding affinity, which contributes to increased insulin resistance High protein intake, especially from animal-based sources, has been associated with an increase in type 2 diabetes risk 29 — The same association was not seen for vegetable protein.
Physical activity and alcohol consumption were constant for each participant throughout the trial. Impaired insulin sensitivity in the obese may attenuate substantial changes in insulin sensitivity brought about by changes in macronutrient intake In our subgroup analyses stratified by weight category, we found that change in QUICKI after consumption of the UNSAT diet was most pronounced in participants of normal weight, and the effect decreases as weight increases.
It is likely that the choice of macronutrient to prevent insulin resistance and type 2 diabetes is less important than overall weight loss in the obese, whereas partial replacement of carbohydrates by unsaturated fat intake can mitigate risk in those of normal weight.
In light of recent evidence suggesting that diabetes in those of normal weight leads to higher mortality 35 , altering macronutrient intake may be another tool in a limited arsenal to combat risk of cardiovascular disease and diabetes in those of normal weight. The main OmniHeart Trial evaluated these three healthy diets differing in macronutrient composition and their comparative effects on blood pressure and lipids 7.
Compared with the CARB diet, which lowered blood pressure and cholesterol from baseline, consumption of the PROT and UNSAT diets further reduced systolic and diastolic blood pressure, and the PROT diet resulted in the greatest reduction in LDL cholesterol.
Rich food sources include spinach, almonds, avocados, cashews and peanuts. Chromium and magnesium may help increase insulin sensitivity.
Evidence shows they may be more effective together. Cinnamon and fenugreek have been used in alternative medicine for thousands of years. They have both been linked to blood sugar control.
The scientific evidence for the use of cinnamon in blood sugar control is mixed. In healthy people, cinnamon has been shown to increase insulin sensitivity and reduce blood sugar spikes following a carb-based meal 43 , 44 , 45 , It found that eating 6 grams of cinnamon with grams of rice pudding significantly reduced blood sugar spikes, compared to eating the pudding alone One review looked at 10 high-quality studies in a total of people with diabetes.
The review found no significant difference in blood sugar spikes after participants had taken cinnamon The European Food Safety Authority EFSA has set the tolerable daily intake of coumarin at 0.
This is around half a teaspoon 1 gram of Cassia cinnamon for a pound kg person One of the properties of fenugreek is that the seeds are high in soluble fiber. An analysis of 10 studies found that fenugreek significantly reduced blood sugar two hours after eating Fenugreek may help reduce blood sugar spikes.
It can be added to food, but it does have quite a strong taste, so some people prefer to take it as a supplement. Both cinnamon and fenugreek are relatively safe. They may have beneficial effects on your blood sugar if you take them with a meal that contains carbs.
Berberine is a chemical that can be extracted from several different plants It has been used in traditional Chinese medicine for thousands of years. Some of its uses include cholesterol reduction, weight loss and blood sugar control 52 , Berberine reduces the amount of sugar produced by the liver and increases insulin sensitivity.
It has even been found to be as effective as some drugs used for type 2 diabetes 54 , 55 , 56 , One study looked at people with type 2 diabetes who either received berberine or a placebo for three months. However, another study found berberine caused side effects in some people, such as diarrhea, constipation and gas Although berberine appears to be fairly safe, speak to your doctor before taking it if you have any medical conditions or are taking any medication.
If you really want to reduce your blood sugar spikes, you should also consider these lifestyle factors that can affect blood sugar. Stress can negatively affect your health in a number of ways, causing headaches, increased blood pressure and anxiety.
It has also been shown to affect blood sugar. As stress levels go up, your body releases certain hormones. The effect is to release stored energy in the form of sugar into your bloodstream for the fight-or-flight response One study of Italian workers found an increase in work-related stress was directly linked to an increase in blood sugar levels Actively addressing stress has also been found to benefit your blood sugar.
In a study of nursing students, yoga exercises were found to reduce stress and blood sugar spikes following a meal Both too little and too much sleep have been associated with poor blood sugar control.
A study of nine healthy people showed that sleeping too little, or only for 4 hours, increased insulin resistance and blood sugar levels With sleep, quality is as important as quantity. A study found the deepest level of sleep NREM to be most important in terms of controlling blood sugar Alcoholic drinks often contain a lot of added sugar.
This is particularly true for mixed drinks and cocktails, which can contain up to 30 grams of sugar per serving. The sugar in alcoholic drinks will cause blood sugar spikes in the same way as added sugar in food. Most alcoholic drinks also have little or no nutritional value. As with added sugar, they are effectively empty calories.
Furthermore, over time, heavy drinking can decrease the effectiveness of insulin, which leads to high blood sugar and can eventually lead to type 2 diabetes However, studies show that moderate, controlled drinking can actually have a protective effect when it comes to blood sugar control and can also lower the risk of developing type 2 diabetes 67 , 68 , Poor sleep, stress and high alcohol intake all negatively affect blood sugar.
Simple dietary changes, such as sticking to a low-carb, high-fiber diet and avoiding added sugars and refined grains, can help you avoid blood sugar spikes. Exercising regularly, maintaining a healthy weight and drinking plenty of water can also have added benefits to your health beyond helping to control your blood sugar.
That said, if you have any medical conditions or are on any medications, speak to your doctor before making any changes to your diet. For most people, making these simple diet and lifestyle changes is a great way to lower your risk of developing insulin resistance or type 2 diabetes.
Our experts continually monitor the health and wellness space, and we update our articles when new information becomes available. This article is based on scientific evidence, written by experts and fact checked by experts.
Our team of licensed nutritionists and dietitians strive to be objective, unbiased, honest and to present both sides of the argument. This article contains scientific references. The numbers in the parentheses 1, 2, 3 are clickable links to peer-reviewed scientific papers.
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Carbohydrates, Carbohyddrate carbs, are naturally found in Responsd foods. For example, grains, sweets, starches, legumes and Carbohysrate all contain Carbohydrate and insulin response amounts of carbs. Metabolism boosting snacks foods and drinks rssponse carbs are digested, the carbs break down into glucose to fuel our cells, and the body's blood glucose, or blood sugar, level rises. In people without diabetes, blood sugar levels rise after eating but the body's insulin response keeps levels from rising too high. If you have diabetes, the process doesn't work as designed. Louis Aronne's study in Diabetes Carbohydrate and insulin response found that insulin Carbohydrate and insulin response glucose Carbouydrate were significantly lower when Carbohgdrate and vegetables Carnohydrate eaten before carbohydrates. Eating protein and Healthy body composition before carbohydrates Carbohydrate and insulin response to insupin post-meal glucose and insulin levels in Carbhydrate patients with type 2 diabetes, Weill Cornell Medical College researchers found in a new study. This finding, published June 23 in the journal Diabetes Care, might impact the way clinicians advise diabetic patients and other high-risk individuals to eat, focusing not only on how much, but also on when carbohydrates are consumed. Louis Aronnethe Sanford I. Weill Professor of Metabolic Research and a professor of clinical medicine at Weill Cornell Medical College, who is the study's principal investigator.
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